{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e3412f9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "de6b34ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dir = \"D:\\\\kaka\\\\new\"\n",
    "fname = os.path.join(data_dir, \"air_quality_data.csv\")\n",
    "f = open(fname,encoding = 'gbk')\n",
    "data = pd.read_csv(f)\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "faf32019",
   "metadata": {},
   "source": [
    "# 数据预处理"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "465271c2",
   "metadata": {},
   "source": [
    "## 查找缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "cac60bbc",
   "metadata": {},
   "outputs": [],
   "source": [
    "null_all = data.isnull().sum()\n",
    "#检测数组data中是否存在缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1e91a111",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OBJECTID    0\n",
       "市代码         0\n",
       "市           0\n",
       "类型          0\n",
       "省           0\n",
       "省代码         0\n",
       "COUNT       1\n",
       "AREA        0\n",
       "MIN         2\n",
       "MAX         0\n",
       "RANGE       1\n",
       "MEAN        1\n",
       "STD         0\n",
       "SUM         1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "null_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d6dc0a35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>市代码</th>\n",
       "      <th>市</th>\n",
       "      <th>类型</th>\n",
       "      <th>省</th>\n",
       "      <th>省代码</th>\n",
       "      <th>COUNT</th>\n",
       "      <th>AREA</th>\n",
       "      <th>MIN</th>\n",
       "      <th>MAX</th>\n",
       "      <th>RANGE</th>\n",
       "      <th>MEAN</th>\n",
       "      <th>STD</th>\n",
       "      <th>SUM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>110000</td>\n",
       "      <td>北京市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>北京市</td>\n",
       "      <td>110000</td>\n",
       "      <td>17345.0</td>\n",
       "      <td>1.7345</td>\n",
       "      <td>21.900000</td>\n",
       "      <td>70.099998</td>\n",
       "      <td>48.199999</td>\n",
       "      <td>45.937896</td>\n",
       "      <td>13.196391</td>\n",
       "      <td>796792.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>110000</td>\n",
       "      <td>北京市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>北京市</td>\n",
       "      <td>110000</td>\n",
       "      <td>17345.0</td>\n",
       "      <td>1.7345</td>\n",
       "      <td>21.900000</td>\n",
       "      <td>70.099998</td>\n",
       "      <td>48.199999</td>\n",
       "      <td>45.937896</td>\n",
       "      <td>13.196391</td>\n",
       "      <td>796792.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>120000</td>\n",
       "      <td>天津市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>天津市</td>\n",
       "      <td>120000</td>\n",
       "      <td>11967.0</td>\n",
       "      <td>1.1967</td>\n",
       "      <td>40.299999</td>\n",
       "      <td>62.700001</td>\n",
       "      <td>22.400002</td>\n",
       "      <td>53.891493</td>\n",
       "      <td>3.736046</td>\n",
       "      <td>644919.500100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>130100</td>\n",
       "      <td>石家庄市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14433.0</td>\n",
       "      <td>1.4433</td>\n",
       "      <td>33.200001</td>\n",
       "      <td>73.400002</td>\n",
       "      <td>40.200001</td>\n",
       "      <td>56.079124</td>\n",
       "      <td>9.697283</td>\n",
       "      <td>809389.999600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>130200</td>\n",
       "      <td>唐山市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14042.0</td>\n",
       "      <td>1.4042</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>29.600002</td>\n",
       "      <td>50.180273</td>\n",
       "      <td>5.142275</td>\n",
       "      <td>704631.399800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>367</td>\n",
       "      <td>659009</td>\n",
       "      <td>昆玉市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>0.1125</td>\n",
       "      <td>28.400000</td>\n",
       "      <td>72.599998</td>\n",
       "      <td>44.199999</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.781729</td>\n",
       "      <td>68603.600070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>368</td>\n",
       "      <td>659010</td>\n",
       "      <td>胡杨河市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>0.1071</td>\n",
       "      <td>23.600000</td>\n",
       "      <td>27.400000</td>\n",
       "      <td>3.799999</td>\n",
       "      <td>25.656676</td>\n",
       "      <td>0.818763</td>\n",
       "      <td>27478.299990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>369</td>\n",
       "      <td>710000</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>不统计</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>710000</td>\n",
       "      <td>31889.0</td>\n",
       "      <td>3.1889</td>\n",
       "      <td>10.700000</td>\n",
       "      <td>26.900000</td>\n",
       "      <td>16.200000</td>\n",
       "      <td>17.353840</td>\n",
       "      <td>3.618578</td>\n",
       "      <td>553396.599800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>370</td>\n",
       "      <td>810000</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>810000</td>\n",
       "      <td>973.0</td>\n",
       "      <td>0.0973</td>\n",
       "      <td>22.100000</td>\n",
       "      <td>26.100000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>23.801644</td>\n",
       "      <td>0.828412</td>\n",
       "      <td>23159.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>371</td>\n",
       "      <td>820000</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>820000</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>27.200001</td>\n",
       "      <td>27.900000</td>\n",
       "      <td>0.699999</td>\n",
       "      <td>27.707692</td>\n",
       "      <td>0.193992</td>\n",
       "      <td>720.399992</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>373 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     OBJECTID     市代码        市     类型         省     省代码    COUNT    AREA  \\\n",
       "0           1  110000      北京市    直辖市       北京市  110000  17345.0  1.7345   \n",
       "1           1  110000      北京市    直辖市       北京市  110000  17345.0  1.7345   \n",
       "2           2  120000      天津市    直辖市       天津市  120000  11967.0  1.1967   \n",
       "3           3  130100     石家庄市    地级市       河北省  130000  14433.0  1.4433   \n",
       "4           4  130200      唐山市    地级市       河北省  130000  14042.0  1.4042   \n",
       "..        ...     ...      ...    ...       ...     ...      ...     ...   \n",
       "368       367  659009      昆玉市   省直辖县  新疆维吾尔自治区  650000   1125.0  0.1125   \n",
       "369       368  659010     胡杨河市   省直辖县  新疆维吾尔自治区  650000   1071.0  0.1071   \n",
       "370       369  710000      台湾省    不统计       台湾省  710000  31889.0  3.1889   \n",
       "371       370  810000  香港特别行政区  特别行政区   香港特别行政区  810000    973.0  0.0973   \n",
       "372       371  820000  澳门特别行政区  特别行政区   澳门特别行政区  820000     26.0  0.0026   \n",
       "\n",
       "           MIN        MAX      RANGE       MEAN        STD            SUM  \n",
       "0    21.900000  70.099998  48.199999  45.937896  13.196391  796792.800000  \n",
       "1    21.900000  70.099998  48.199999  45.937896  13.196391  796792.800000  \n",
       "2    40.299999  62.700001  22.400002  53.891493   3.736046  644919.500100  \n",
       "3    33.200001  73.400002  40.200001  56.079124   9.697283  809389.999600  \n",
       "4     1.000000  63.900002  29.600002  50.180273   5.142275  704631.399800  \n",
       "..         ...        ...        ...        ...        ...            ...  \n",
       "368  28.400000  72.599998  44.199999   1.000000   6.781729   68603.600070  \n",
       "369  23.600000  27.400000   3.799999  25.656676   0.818763   27478.299990  \n",
       "370  10.700000  26.900000  16.200000  17.353840   3.618578  553396.599800  \n",
       "371  22.100000  26.100000   4.000000  23.801644   0.828412   23159.000000  \n",
       "372  27.200001  27.900000   0.699999  27.707692   0.193992     720.399992  \n",
       "\n",
       "[373 rows x 14 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#为处理数据集中的缺失值，一般采用填充的方式\n",
    "#全局常量填充缺失值\n",
    "data.fillna(1)\n",
    "#即所有的缺失值都使用一个常量进行填充，例如此处采用的便是1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b1c4f4a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>市代码</th>\n",
       "      <th>市</th>\n",
       "      <th>类型</th>\n",
       "      <th>省</th>\n",
       "      <th>省代码</th>\n",
       "      <th>COUNT</th>\n",
       "      <th>AREA</th>\n",
       "      <th>MIN</th>\n",
       "      <th>MAX</th>\n",
       "      <th>RANGE</th>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>110000</td>\n",
       "      <td>北京市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>北京市</td>\n",
       "      <td>110000</td>\n",
       "      <td>17345.0</td>\n",
       "      <td>1.7345</td>\n",
       "      <td>21.900000</td>\n",
       "      <td>70.099998</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>110000</td>\n",
       "      <td>北京市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>北京市</td>\n",
       "      <td>110000</td>\n",
       "      <td>17345.0</td>\n",
       "      <td>1.7345</td>\n",
       "      <td>21.900000</td>\n",
       "      <td>70.099998</td>\n",
       "      <td>48.199999</td>\n",
       "      <td>45.937896</td>\n",
       "      <td>13.196391</td>\n",
       "      <td>796792.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>120000</td>\n",
       "      <td>天津市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>天津市</td>\n",
       "      <td>120000</td>\n",
       "      <td>11967.0</td>\n",
       "      <td>1.1967</td>\n",
       "      <td>40.299999</td>\n",
       "      <td>62.700001</td>\n",
       "      <td>22.400002</td>\n",
       "      <td>53.891493</td>\n",
       "      <td>3.736046</td>\n",
       "      <td>644919.500100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>130100</td>\n",
       "      <td>石家庄市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14433.0</td>\n",
       "      <td>1.4433</td>\n",
       "      <td>33.200001</td>\n",
       "      <td>73.400002</td>\n",
       "      <td>40.200001</td>\n",
       "      <td>56.079124</td>\n",
       "      <td>9.697283</td>\n",
       "      <td>809389.999600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>130200</td>\n",
       "      <td>唐山市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14042.0</td>\n",
       "      <td>1.4042</td>\n",
       "      <td>33.200001</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>29.600002</td>\n",
       "      <td>50.180273</td>\n",
       "      <td>5.142275</td>\n",
       "      <td>704631.399800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>367</td>\n",
       "      <td>659009</td>\n",
       "      <td>昆玉市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>0.1125</td>\n",
       "      <td>28.400000</td>\n",
       "      <td>72.599998</td>\n",
       "      <td>44.199999</td>\n",
       "      <td>29.054427</td>\n",
       "      <td>6.781729</td>\n",
       "      <td>68603.600070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>368</td>\n",
       "      <td>659010</td>\n",
       "      <td>胡杨河市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>0.1071</td>\n",
       "      <td>23.600000</td>\n",
       "      <td>27.400000</td>\n",
       "      <td>3.799999</td>\n",
       "      <td>25.656676</td>\n",
       "      <td>0.818763</td>\n",
       "      <td>27478.299990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>369</td>\n",
       "      <td>710000</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>不统计</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>710000</td>\n",
       "      <td>31889.0</td>\n",
       "      <td>3.1889</td>\n",
       "      <td>10.700000</td>\n",
       "      <td>26.900000</td>\n",
       "      <td>16.200000</td>\n",
       "      <td>17.353840</td>\n",
       "      <td>3.618578</td>\n",
       "      <td>553396.599800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>370</td>\n",
       "      <td>810000</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>810000</td>\n",
       "      <td>973.0</td>\n",
       "      <td>0.0973</td>\n",
       "      <td>22.100000</td>\n",
       "      <td>26.100000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>23.801644</td>\n",
       "      <td>0.828412</td>\n",
       "      <td>23159.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>371</td>\n",
       "      <td>820000</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>820000</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>27.200001</td>\n",
       "      <td>27.900000</td>\n",
       "      <td>0.699999</td>\n",
       "      <td>27.707692</td>\n",
       "      <td>0.193992</td>\n",
       "      <td>720.399992</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>373 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     OBJECTID     市代码        市     类型         省     省代码    COUNT    AREA  \\\n",
       "0           1  110000      北京市    直辖市       北京市  110000  17345.0  1.7345   \n",
       "1           1  110000      北京市    直辖市       北京市  110000  17345.0  1.7345   \n",
       "2           2  120000      天津市    直辖市       天津市  120000  11967.0  1.1967   \n",
       "3           3  130100     石家庄市    地级市       河北省  130000  14433.0  1.4433   \n",
       "4           4  130200      唐山市    地级市       河北省  130000  14042.0  1.4042   \n",
       "..        ...     ...      ...    ...       ...     ...      ...     ...   \n",
       "368       367  659009      昆玉市   省直辖县  新疆维吾尔自治区  650000   1125.0  0.1125   \n",
       "369       368  659010     胡杨河市   省直辖县  新疆维吾尔自治区  650000   1071.0  0.1071   \n",
       "370       369  710000      台湾省    不统计       台湾省  710000  31889.0  3.1889   \n",
       "371       370  810000  香港特别行政区  特别行政区   香港特别行政区  810000    973.0  0.0973   \n",
       "372       371  820000  澳门特别行政区  特别行政区   澳门特别行政区  820000     26.0  0.0026   \n",
       "\n",
       "           MIN        MAX      RANGE       MEAN        STD            SUM  \n",
       "0    21.900000  70.099998  48.199999  45.937896  13.196391  796792.800000  \n",
       "1    21.900000  70.099998  48.199999  45.937896  13.196391  796792.800000  \n",
       "2    40.299999  62.700001  22.400002  53.891493   3.736046  644919.500100  \n",
       "3    33.200001  73.400002  40.200001  56.079124   9.697283  809389.999600  \n",
       "4    33.200001  63.900002  29.600002  50.180273   5.142275  704631.399800  \n",
       "..         ...        ...        ...        ...        ...            ...  \n",
       "368  28.400000  72.599998  44.199999  29.054427   6.781729   68603.600070  \n",
       "369  23.600000  27.400000   3.799999  25.656676   0.818763   27478.299990  \n",
       "370  10.700000  26.900000  16.200000  17.353840   3.618578  553396.599800  \n",
       "371  22.100000  26.100000   4.000000  23.801644   0.828412   23159.000000  \n",
       "372  27.200001  27.900000   0.699999  27.707692   0.193992     720.399992  \n",
       "\n",
       "[373 rows x 14 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#前填充和后填充，即使用缺失值的前一个文字的值或者后一个位置的值进行填充\n",
    "data.fillna(method='ffill')    # ffill---前填充；bfill--后填充"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "581a93c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>市代码</th>\n",
       "      <th>市</th>\n",
       "      <th>类型</th>\n",
       "      <th>省</th>\n",
       "      <th>省代码</th>\n",
       "      <th>COUNT</th>\n",
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       "      <th>0</th>\n",
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       "      <td>110000</td>\n",
       "      <td>北京市</td>\n",
       "      <td>直辖市</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>110000</td>\n",
       "      <td>北京市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>北京市</td>\n",
       "      <td>110000</td>\n",
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       "      <td>13.196391</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>120000</td>\n",
       "      <td>天津市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>天津市</td>\n",
       "      <td>120000</td>\n",
       "      <td>11967.0</td>\n",
       "      <td>1.1967</td>\n",
       "      <td>40.299999</td>\n",
       "      <td>62.700001</td>\n",
       "      <td>22.400002</td>\n",
       "      <td>53.891493</td>\n",
       "      <td>3.736046</td>\n",
       "      <td>644919.500100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>130100</td>\n",
       "      <td>石家庄市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14433.0</td>\n",
       "      <td>1.4433</td>\n",
       "      <td>33.200001</td>\n",
       "      <td>73.400002</td>\n",
       "      <td>40.200001</td>\n",
       "      <td>56.079124</td>\n",
       "      <td>9.697283</td>\n",
       "      <td>809389.999600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>130200</td>\n",
       "      <td>唐山市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14042.0</td>\n",
       "      <td>1.4042</td>\n",
       "      <td>27.100000</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>29.600002</td>\n",
       "      <td>50.180273</td>\n",
       "      <td>5.142275</td>\n",
       "      <td>704631.399800</td>\n",
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       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>367</td>\n",
       "      <td>659009</td>\n",
       "      <td>昆玉市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>0.1125</td>\n",
       "      <td>28.400000</td>\n",
       "      <td>72.599998</td>\n",
       "      <td>44.199999</td>\n",
       "      <td>25.656676</td>\n",
       "      <td>6.781729</td>\n",
       "      <td>68603.600070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>368</td>\n",
       "      <td>659010</td>\n",
       "      <td>胡杨河市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>0.1071</td>\n",
       "      <td>23.600000</td>\n",
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       "      <td>0.818763</td>\n",
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       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>369</td>\n",
       "      <td>710000</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>不统计</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>710000</td>\n",
       "      <td>31889.0</td>\n",
       "      <td>3.1889</td>\n",
       "      <td>10.700000</td>\n",
       "      <td>26.900000</td>\n",
       "      <td>16.200000</td>\n",
       "      <td>17.353840</td>\n",
       "      <td>3.618578</td>\n",
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       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>370</td>\n",
       "      <td>810000</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>810000</td>\n",
       "      <td>973.0</td>\n",
       "      <td>0.0973</td>\n",
       "      <td>22.100000</td>\n",
       "      <td>26.100000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>23.801644</td>\n",
       "      <td>0.828412</td>\n",
       "      <td>23159.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>371</td>\n",
       "      <td>820000</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>820000</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>27.200001</td>\n",
       "      <td>27.900000</td>\n",
       "      <td>0.699999</td>\n",
       "      <td>27.707692</td>\n",
       "      <td>0.193992</td>\n",
       "      <td>720.399992</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>373 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     OBJECTID     市代码        市     类型         省     省代码    COUNT    AREA  \\\n",
       "0           1  110000      北京市    直辖市       北京市  110000  17345.0  1.7345   \n",
       "1           1  110000      北京市    直辖市       北京市  110000  17345.0  1.7345   \n",
       "2           2  120000      天津市    直辖市       天津市  120000  11967.0  1.1967   \n",
       "3           3  130100     石家庄市    地级市       河北省  130000  14433.0  1.4433   \n",
       "4           4  130200      唐山市    地级市       河北省  130000  14042.0  1.4042   \n",
       "..        ...     ...      ...    ...       ...     ...      ...     ...   \n",
       "368       367  659009      昆玉市   省直辖县  新疆维吾尔自治区  650000   1125.0  0.1125   \n",
       "369       368  659010     胡杨河市   省直辖县  新疆维吾尔自治区  650000   1071.0  0.1071   \n",
       "370       369  710000      台湾省    不统计       台湾省  710000  31889.0  3.1889   \n",
       "371       370  810000  香港特别行政区  特别行政区   香港特别行政区  810000    973.0  0.0973   \n",
       "372       371  820000  澳门特别行政区  特别行政区   澳门特别行政区  820000     26.0  0.0026   \n",
       "\n",
       "           MIN        MAX      RANGE       MEAN        STD            SUM  \n",
       "0    21.900000  70.099998  48.199999  45.937896  13.196391  796792.800000  \n",
       "1    21.900000  70.099998  48.199999  45.937896  13.196391  796792.800000  \n",
       "2    40.299999  62.700001  22.400002  53.891493   3.736046  644919.500100  \n",
       "3    33.200001  73.400002  40.200001  56.079124   9.697283  809389.999600  \n",
       "4    27.100000  63.900002  29.600002  50.180273   5.142275  704631.399800  \n",
       "..         ...        ...        ...        ...        ...            ...  \n",
       "368  28.400000  72.599998  44.199999  25.656676   6.781729   68603.600070  \n",
       "369  23.600000  27.400000   3.799999  25.656676   0.818763   27478.299990  \n",
       "370  10.700000  26.900000  16.200000  17.353840   3.618578  553396.599800  \n",
       "371  22.100000  26.100000   4.000000  23.801644   0.828412   23159.000000  \n",
       "372  27.200001  27.900000   0.699999  27.707692   0.193992     720.399992  \n",
       "\n",
       "[373 rows x 14 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.fillna(method='bfill')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4107893f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\kaka\\AppData\\Local\\Temp/ipykernel_19352/197123336.py:2: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError.  Select only valid columns before calling the reduction.\n",
      "  data.fillna(data.mean())\n"
     ]
    },
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       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>120000</td>\n",
       "      <td>天津市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>天津市</td>\n",
       "      <td>120000</td>\n",
       "      <td>11967.0</td>\n",
       "      <td>1.1967</td>\n",
       "      <td>40.299999</td>\n",
       "      <td>62.700001</td>\n",
       "      <td>22.400002</td>\n",
       "      <td>53.891493</td>\n",
       "      <td>3.736046</td>\n",
       "      <td>644919.500100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>130100</td>\n",
       "      <td>石家庄市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14433.0</td>\n",
       "      <td>1.4433</td>\n",
       "      <td>33.200001</td>\n",
       "      <td>73.400002</td>\n",
       "      <td>40.200001</td>\n",
       "      <td>56.079124</td>\n",
       "      <td>9.697283</td>\n",
       "      <td>809389.999600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>130200</td>\n",
       "      <td>唐山市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14042.0</td>\n",
       "      <td>1.4042</td>\n",
       "      <td>23.703774</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>29.600002</td>\n",
       "      <td>50.180273</td>\n",
       "      <td>5.142275</td>\n",
       "      <td>704631.399800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>367</td>\n",
       "      <td>659009</td>\n",
       "      <td>昆玉市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>0.1125</td>\n",
       "      <td>28.400000</td>\n",
       "      <td>72.599998</td>\n",
       "      <td>44.199999</td>\n",
       "      <td>31.720557</td>\n",
       "      <td>6.781729</td>\n",
       "      <td>68603.600070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>368</td>\n",
       "      <td>659010</td>\n",
       "      <td>胡杨河市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>0.1071</td>\n",
       "      <td>23.600000</td>\n",
       "      <td>27.400000</td>\n",
       "      <td>3.799999</td>\n",
       "      <td>25.656676</td>\n",
       "      <td>0.818763</td>\n",
       "      <td>27478.299990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>369</td>\n",
       "      <td>710000</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>不统计</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>710000</td>\n",
       "      <td>31889.0</td>\n",
       "      <td>3.1889</td>\n",
       "      <td>10.700000</td>\n",
       "      <td>26.900000</td>\n",
       "      <td>16.200000</td>\n",
       "      <td>17.353840</td>\n",
       "      <td>3.618578</td>\n",
       "      <td>553396.599800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>370</td>\n",
       "      <td>810000</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>810000</td>\n",
       "      <td>973.0</td>\n",
       "      <td>0.0973</td>\n",
       "      <td>22.100000</td>\n",
       "      <td>26.100000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>23.801644</td>\n",
       "      <td>0.828412</td>\n",
       "      <td>23159.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>371</td>\n",
       "      <td>820000</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>820000</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>27.200001</td>\n",
       "      <td>27.900000</td>\n",
       "      <td>0.699999</td>\n",
       "      <td>27.707692</td>\n",
       "      <td>0.193992</td>\n",
       "      <td>720.399992</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>373 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     OBJECTID     市代码        市     类型         省     省代码    COUNT    AREA  \\\n",
       "0           1  110000      北京市    直辖市       北京市  110000  17345.0  1.7345   \n",
       "1           1  110000      北京市    直辖市       北京市  110000  17345.0  1.7345   \n",
       "2           2  120000      天津市    直辖市       天津市  120000  11967.0  1.1967   \n",
       "3           3  130100     石家庄市    地级市       河北省  130000  14433.0  1.4433   \n",
       "4           4  130200      唐山市    地级市       河北省  130000  14042.0  1.4042   \n",
       "..        ...     ...      ...    ...       ...     ...      ...     ...   \n",
       "368       367  659009      昆玉市   省直辖县  新疆维吾尔自治区  650000   1125.0  0.1125   \n",
       "369       368  659010     胡杨河市   省直辖县  新疆维吾尔自治区  650000   1071.0  0.1071   \n",
       "370       369  710000      台湾省    不统计       台湾省  710000  31889.0  3.1889   \n",
       "371       370  810000  香港特别行政区  特别行政区   香港特别行政区  810000    973.0  0.0973   \n",
       "372       371  820000  澳门特别行政区  特别行政区   澳门特别行政区  820000     26.0  0.0026   \n",
       "\n",
       "           MIN        MAX      RANGE       MEAN        STD            SUM  \n",
       "0    21.900000  70.099998  48.199999  45.937896  13.196391  796792.800000  \n",
       "1    21.900000  70.099998  48.199999  45.937896  13.196391  796792.800000  \n",
       "2    40.299999  62.700001  22.400002  53.891493   3.736046  644919.500100  \n",
       "3    33.200001  73.400002  40.200001  56.079124   9.697283  809389.999600  \n",
       "4    23.703774  63.900002  29.600002  50.180273   5.142275  704631.399800  \n",
       "..         ...        ...        ...        ...        ...            ...  \n",
       "368  28.400000  72.599998  44.199999  31.720557   6.781729   68603.600070  \n",
       "369  23.600000  27.400000   3.799999  25.656676   0.818763   27478.299990  \n",
       "370  10.700000  26.900000  16.200000  17.353840   3.618578  553396.599800  \n",
       "371  22.100000  26.100000   4.000000  23.801644   0.828412   23159.000000  \n",
       "372  27.200001  27.900000   0.699999  27.707692   0.193992     720.399992  \n",
       "\n",
       "[373 rows x 14 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#均值填充\n",
    "data.fillna(data.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "dda0d3f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\kaka\\AppData\\Local\\Temp/ipykernel_19352/1041076789.py:2: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError.  Select only valid columns before calling the reduction.\n",
      "  data.fillna(data.median())\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>市代码</th>\n",
       "      <th>市</th>\n",
       "      <th>类型</th>\n",
       "      <th>省</th>\n",
       "      <th>省代码</th>\n",
       "      <th>COUNT</th>\n",
       "      <th>AREA</th>\n",
       "      <th>MIN</th>\n",
       "      <th>MAX</th>\n",
       "      <th>RANGE</th>\n",
       "      <th>MEAN</th>\n",
       "      <th>STD</th>\n",
       "      <th>SUM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>110000</td>\n",
       "      <td>北京市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>北京市</td>\n",
       "      <td>110000</td>\n",
       "      <td>17345.0</td>\n",
       "      <td>1.7345</td>\n",
       "      <td>21.900000</td>\n",
       "      <td>70.099998</td>\n",
       "      <td>48.199999</td>\n",
       "      <td>45.937896</td>\n",
       "      <td>13.196391</td>\n",
       "      <td>796792.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>110000</td>\n",
       "      <td>北京市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>北京市</td>\n",
       "      <td>110000</td>\n",
       "      <td>17345.0</td>\n",
       "      <td>1.7345</td>\n",
       "      <td>21.900000</td>\n",
       "      <td>70.099998</td>\n",
       "      <td>48.199999</td>\n",
       "      <td>45.937896</td>\n",
       "      <td>13.196391</td>\n",
       "      <td>796792.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>120000</td>\n",
       "      <td>天津市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>天津市</td>\n",
       "      <td>120000</td>\n",
       "      <td>11967.0</td>\n",
       "      <td>1.1967</td>\n",
       "      <td>40.299999</td>\n",
       "      <td>62.700001</td>\n",
       "      <td>22.400002</td>\n",
       "      <td>53.891493</td>\n",
       "      <td>3.736046</td>\n",
       "      <td>644919.500100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>130100</td>\n",
       "      <td>石家庄市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14433.0</td>\n",
       "      <td>1.4433</td>\n",
       "      <td>33.200001</td>\n",
       "      <td>73.400002</td>\n",
       "      <td>40.200001</td>\n",
       "      <td>56.079124</td>\n",
       "      <td>9.697283</td>\n",
       "      <td>809389.999600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>130200</td>\n",
       "      <td>唐山市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14042.0</td>\n",
       "      <td>1.4042</td>\n",
       "      <td>23.100000</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>29.600002</td>\n",
       "      <td>50.180273</td>\n",
       "      <td>5.142275</td>\n",
       "      <td>704631.399800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>367</td>\n",
       "      <td>659009</td>\n",
       "      <td>昆玉市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>0.1125</td>\n",
       "      <td>28.400000</td>\n",
       "      <td>72.599998</td>\n",
       "      <td>44.199999</td>\n",
       "      <td>30.799311</td>\n",
       "      <td>6.781729</td>\n",
       "      <td>68603.600070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>368</td>\n",
       "      <td>659010</td>\n",
       "      <td>胡杨河市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>0.1071</td>\n",
       "      <td>23.600000</td>\n",
       "      <td>27.400000</td>\n",
       "      <td>3.799999</td>\n",
       "      <td>25.656676</td>\n",
       "      <td>0.818763</td>\n",
       "      <td>27478.299990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>369</td>\n",
       "      <td>710000</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>不统计</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>710000</td>\n",
       "      <td>31889.0</td>\n",
       "      <td>3.1889</td>\n",
       "      <td>10.700000</td>\n",
       "      <td>26.900000</td>\n",
       "      <td>16.200000</td>\n",
       "      <td>17.353840</td>\n",
       "      <td>3.618578</td>\n",
       "      <td>553396.599800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>370</td>\n",
       "      <td>810000</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>810000</td>\n",
       "      <td>973.0</td>\n",
       "      <td>0.0973</td>\n",
       "      <td>22.100000</td>\n",
       "      <td>26.100000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>23.801644</td>\n",
       "      <td>0.828412</td>\n",
       "      <td>23159.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>371</td>\n",
       "      <td>820000</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>820000</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>27.200001</td>\n",
       "      <td>27.900000</td>\n",
       "      <td>0.699999</td>\n",
       "      <td>27.707692</td>\n",
       "      <td>0.193992</td>\n",
       "      <td>720.399992</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>373 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     OBJECTID     市代码        市     类型         省     省代码    COUNT    AREA  \\\n",
       "0           1  110000      北京市    直辖市       北京市  110000  17345.0  1.7345   \n",
       "1           1  110000      北京市    直辖市       北京市  110000  17345.0  1.7345   \n",
       "2           2  120000      天津市    直辖市       天津市  120000  11967.0  1.1967   \n",
       "3           3  130100     石家庄市    地级市       河北省  130000  14433.0  1.4433   \n",
       "4           4  130200      唐山市    地级市       河北省  130000  14042.0  1.4042   \n",
       "..        ...     ...      ...    ...       ...     ...      ...     ...   \n",
       "368       367  659009      昆玉市   省直辖县  新疆维吾尔自治区  650000   1125.0  0.1125   \n",
       "369       368  659010     胡杨河市   省直辖县  新疆维吾尔自治区  650000   1071.0  0.1071   \n",
       "370       369  710000      台湾省    不统计       台湾省  710000  31889.0  3.1889   \n",
       "371       370  810000  香港特别行政区  特别行政区   香港特别行政区  810000    973.0  0.0973   \n",
       "372       371  820000  澳门特别行政区  特别行政区   澳门特别行政区  820000     26.0  0.0026   \n",
       "\n",
       "           MIN        MAX      RANGE       MEAN        STD            SUM  \n",
       "0    21.900000  70.099998  48.199999  45.937896  13.196391  796792.800000  \n",
       "1    21.900000  70.099998  48.199999  45.937896  13.196391  796792.800000  \n",
       "2    40.299999  62.700001  22.400002  53.891493   3.736046  644919.500100  \n",
       "3    33.200001  73.400002  40.200001  56.079124   9.697283  809389.999600  \n",
       "4    23.100000  63.900002  29.600002  50.180273   5.142275  704631.399800  \n",
       "..         ...        ...        ...        ...        ...            ...  \n",
       "368  28.400000  72.599998  44.199999  30.799311   6.781729   68603.600070  \n",
       "369  23.600000  27.400000   3.799999  25.656676   0.818763   27478.299990  \n",
       "370  10.700000  26.900000  16.200000  17.353840   3.618578  553396.599800  \n",
       "371  22.100000  26.100000   4.000000  23.801644   0.828412   23159.000000  \n",
       "372  27.200001  27.900000   0.699999  27.707692   0.193992     720.399992  \n",
       "\n",
       "[373 rows x 14 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#中位数填充\n",
    "data.fillna(data.median())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "93cb40de",
   "metadata": {},
   "outputs": [],
   "source": [
    "#插值法\n",
    "#利用缺失值前后两个数的平均值进行填充\n",
    "data.interpolate()\n",
    "data = data.interpolate()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2e6460c",
   "metadata": {},
   "source": [
    "# 重复值处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f51c4c07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      False\n",
       "1       True\n",
       "2      False\n",
       "3      False\n",
       "4      False\n",
       "       ...  \n",
       "368    False\n",
       "369    False\n",
       "370    False\n",
       "371    False\n",
       "372    False\n",
       "Length: 373, dtype: bool"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#重复值判断\n",
    "data.duplicated()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cdecbfce",
   "metadata": {},
   "outputs": [],
   "source": [
    "#重复值的删除\n",
    "data.drop_duplicates(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "221488f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>市代码</th>\n",
       "      <th>市</th>\n",
       "      <th>类型</th>\n",
       "      <th>省</th>\n",
       "      <th>省代码</th>\n",
       "      <th>COUNT</th>\n",
       "      <th>AREA</th>\n",
       "      <th>MIN</th>\n",
       "      <th>MAX</th>\n",
       "      <th>RANGE</th>\n",
       "      <th>MEAN</th>\n",
       "      <th>STD</th>\n",
       "      <th>SUM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>110000</td>\n",
       "      <td>北京市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>北京市</td>\n",
       "      <td>110000</td>\n",
       "      <td>17345.0</td>\n",
       "      <td>1.7345</td>\n",
       "      <td>21.900000</td>\n",
       "      <td>70.099998</td>\n",
       "      <td>48.199999</td>\n",
       "      <td>45.937896</td>\n",
       "      <td>13.196391</td>\n",
       "      <td>796792.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>120000</td>\n",
       "      <td>天津市</td>\n",
       "      <td>直辖市</td>\n",
       "      <td>天津市</td>\n",
       "      <td>120000</td>\n",
       "      <td>11967.0</td>\n",
       "      <td>1.1967</td>\n",
       "      <td>40.299999</td>\n",
       "      <td>62.700001</td>\n",
       "      <td>22.400002</td>\n",
       "      <td>53.891493</td>\n",
       "      <td>3.736046</td>\n",
       "      <td>644919.500100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>130100</td>\n",
       "      <td>石家庄市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14433.0</td>\n",
       "      <td>1.4433</td>\n",
       "      <td>33.200001</td>\n",
       "      <td>73.400002</td>\n",
       "      <td>40.200001</td>\n",
       "      <td>56.079124</td>\n",
       "      <td>9.697283</td>\n",
       "      <td>809389.999600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>130200</td>\n",
       "      <td>唐山市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>14042.0</td>\n",
       "      <td>1.4042</td>\n",
       "      <td>30.150001</td>\n",
       "      <td>63.900002</td>\n",
       "      <td>29.600002</td>\n",
       "      <td>50.180273</td>\n",
       "      <td>5.142275</td>\n",
       "      <td>704631.399800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>130300</td>\n",
       "      <td>秦皇岛市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>130000</td>\n",
       "      <td>13089.0</td>\n",
       "      <td>0.8223</td>\n",
       "      <td>27.100000</td>\n",
       "      <td>49.200001</td>\n",
       "      <td>22.100000</td>\n",
       "      <td>36.955089</td>\n",
       "      <td>4.732128</td>\n",
       "      <td>303881.699900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>367</td>\n",
       "      <td>659009</td>\n",
       "      <td>昆玉市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1125.0</td>\n",
       "      <td>0.1125</td>\n",
       "      <td>28.400000</td>\n",
       "      <td>72.599998</td>\n",
       "      <td>44.199999</td>\n",
       "      <td>27.355552</td>\n",
       "      <td>6.781729</td>\n",
       "      <td>68603.600070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>368</td>\n",
       "      <td>659010</td>\n",
       "      <td>胡杨河市</td>\n",
       "      <td>省直辖县</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>650000</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>0.1071</td>\n",
       "      <td>23.600000</td>\n",
       "      <td>27.400000</td>\n",
       "      <td>3.799999</td>\n",
       "      <td>25.656676</td>\n",
       "      <td>0.818763</td>\n",
       "      <td>27478.299990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>369</td>\n",
       "      <td>710000</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>不统计</td>\n",
       "      <td>台湾省</td>\n",
       "      <td>710000</td>\n",
       "      <td>31889.0</td>\n",
       "      <td>3.1889</td>\n",
       "      <td>10.700000</td>\n",
       "      <td>26.900000</td>\n",
       "      <td>16.200000</td>\n",
       "      <td>17.353840</td>\n",
       "      <td>3.618578</td>\n",
       "      <td>553396.599800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>370</td>\n",
       "      <td>810000</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>香港特别行政区</td>\n",
       "      <td>810000</td>\n",
       "      <td>973.0</td>\n",
       "      <td>0.0973</td>\n",
       "      <td>22.100000</td>\n",
       "      <td>26.100000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>23.801644</td>\n",
       "      <td>0.828412</td>\n",
       "      <td>23159.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>371</td>\n",
       "      <td>820000</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>特别行政区</td>\n",
       "      <td>澳门特别行政区</td>\n",
       "      <td>820000</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>27.200001</td>\n",
       "      <td>27.900000</td>\n",
       "      <td>0.699999</td>\n",
       "      <td>27.707692</td>\n",
       "      <td>0.193992</td>\n",
       "      <td>720.399992</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>372 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     OBJECTID     市代码        市     类型         省     省代码    COUNT    AREA  \\\n",
       "0           1  110000      北京市    直辖市       北京市  110000  17345.0  1.7345   \n",
       "2           2  120000      天津市    直辖市       天津市  120000  11967.0  1.1967   \n",
       "3           3  130100     石家庄市    地级市       河北省  130000  14433.0  1.4433   \n",
       "4           4  130200      唐山市    地级市       河北省  130000  14042.0  1.4042   \n",
       "5           5  130300     秦皇岛市    地级市       河北省  130000  13089.0  0.8223   \n",
       "..        ...     ...      ...    ...       ...     ...      ...     ...   \n",
       "368       367  659009      昆玉市   省直辖县  新疆维吾尔自治区  650000   1125.0  0.1125   \n",
       "369       368  659010     胡杨河市   省直辖县  新疆维吾尔自治区  650000   1071.0  0.1071   \n",
       "370       369  710000      台湾省    不统计       台湾省  710000  31889.0  3.1889   \n",
       "371       370  810000  香港特别行政区  特别行政区   香港特别行政区  810000    973.0  0.0973   \n",
       "372       371  820000  澳门特别行政区  特别行政区   澳门特别行政区  820000     26.0  0.0026   \n",
       "\n",
       "           MIN        MAX      RANGE       MEAN        STD            SUM  \n",
       "0    21.900000  70.099998  48.199999  45.937896  13.196391  796792.800000  \n",
       "2    40.299999  62.700001  22.400002  53.891493   3.736046  644919.500100  \n",
       "3    33.200001  73.400002  40.200001  56.079124   9.697283  809389.999600  \n",
       "4    30.150001  63.900002  29.600002  50.180273   5.142275  704631.399800  \n",
       "5    27.100000  49.200001  22.100000  36.955089   4.732128  303881.699900  \n",
       "..         ...        ...        ...        ...        ...            ...  \n",
       "368  28.400000  72.599998  44.199999  27.355552   6.781729   68603.600070  \n",
       "369  23.600000  27.400000   3.799999  25.656676   0.818763   27478.299990  \n",
       "370  10.700000  26.900000  16.200000  17.353840   3.618578  553396.599800  \n",
       "371  22.100000  26.100000   4.000000  23.801644   0.828412   23159.000000  \n",
       "372  27.200001  27.900000   0.699999  27.707692   0.193992     720.399992  \n",
       "\n",
       "[372 rows x 14 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c7e8550",
   "metadata": {},
   "source": [
    "# 数据转换"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16835137",
   "metadata": {},
   "source": [
    "## 数据标准化 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cf4b87b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "标准化之前方差： [1.5 1.5 1.5 1.5]\n",
      "标准化之前标准差： [1.11803399 1.11803399 1.11803399 1.11803399]\n",
      "\n",
      "标准化后结果：\n",
      " [[ 1.34164079  1.34164079  0.4472136  -0.4472136 ]\n",
      " [ 0.4472136  -1.34164079 -1.34164079  0.4472136 ]\n",
      " [-1.34164079 -0.4472136  -0.4472136   1.34164079]\n",
      " [-0.4472136   0.4472136   1.34164079 -1.34164079]]\n",
      "\n",
      "标准化之后方差： [-1.38777878e-17  0.00000000e+00  0.00000000e+00  0.00000000e+00]\n",
      "标准化之后标准差： [1. 1. 1. 1.]\n"
     ]
    }
   ],
   "source": [
    "from sklearn import preprocessing\n",
    "import numpy as np\n",
    " \n",
    "x = np.array([[3., 3, 2., 1],\n",
    "              [2., 0., 0., 2],\n",
    "              [0., 1., 1., 3],\n",
    "              [1., 2., 3, 0]])\n",
    " \n",
    "print(\"标准化之前方差：\", x.mean(axis=0))\n",
    "print(\"标准化之前标准差：\", x.std(axis=0))\n",
    " \n",
    "#标准化\n",
    "x_scale = preprocessing.scale(x)\n",
    "print(\"\\n标准化后结果：\\n\", x_scale)\n",
    "# 这里输出应该是【0,0,0,0】\n",
    "print(\"\\n标准化之后方差：\", x_scale.mean(axis=0))\n",
    "# 这里输出应该是【1,1,1,1】\n",
    "print(\"标准化之后标准差：\", x_scale.std(axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "05ad64eb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1.         1.         0.66666667 0.33333333]\n",
      " [0.66666667 0.         0.         0.66666667]\n",
      " [0.         0.33333333 0.33333333 1.        ]\n",
      " [0.33333333 0.66666667 1.         0.        ]]\n"
     ]
    }
   ],
   "source": [
    "#Min-Max标准化\n",
    "#将数值转化为[0,1]之间\n",
    "from sklearn import preprocessing\n",
    "import numpy as np\n",
    " \n",
    "x = np.array([[3., 3, 2., 1],\n",
    "              [2., 0., 0., 2],\n",
    "              [0., 1., 1., 3],\n",
    "              [1., 2., 3, 0]])\n",
    " \n",
    "min_max_scaler = preprocessing.MinMaxScaler()\n",
    "x_minmax = min_max_scaler.fit_transform(x)\n",
    "print(x_minmax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "47c87bba",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Z_Score标准化:[-1.5492 -1.1619 -0.7746 -0.3873  0.      0.3873  0.7746  1.1619  1.5492]\n"
     ]
    }
   ],
   "source": [
    "#Z-Score标准化\n",
    "class Datanorm:\n",
    "    def __init__(self):\n",
    "        self.arr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])\n",
    "        self.x_max = self.arr.max() #数组元素中的最大值\n",
    "        self.x_min = self.arr.min() #数组元素中的最小值\n",
    "        self.x_mean = self.arr.mean() # 数组元素中平均值\n",
    "        self.x_std = self.arr.std() #数组元素中的标准差\n",
    "\n",
    "    def Z_ScoreNorm(self):\n",
    "        arr = np.around((self.arr - self.x_mean) / self.x_std, decimals=4)\n",
    "        print(\"Z_Score标准化:{}\".format(arr))\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    a = Datanorm()\n",
    "    a.Z_ScoreNorm()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd85a6ba",
   "metadata": {},
   "source": [
    "# 数据离散化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "810bd62c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 可视化\n",
    "def cluster_plot(d, k):\n",
    "    import matplotlib.pyplot as plt\n",
    "    plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "    plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "    plt.figure(figsize=(12, 4))\n",
    "    for j in range(0, k):\n",
    "        plt.plot(data.MEAN[d == j], [j for i in d[d == j]], 'o')\n",
    "\n",
    "    plt.ylim(-0.5, k - 0.5)\n",
    "    return plt\n",
    "\n",
    "\n",
    "k = 5 # 分为5个等宽区间\n",
    "# 等宽离散\n",
    "d1 = pd.cut(data.MEAN, k, labels=range(k))\n",
    "cluster_plot(d1, k).show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a4869a01",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2.315, 23.802]     75\n",
      "(41.059, 63.602]    75\n",
      "(23.802, 28.515]    74\n",
      "(28.515, 33.835]    74\n",
      "(33.835, 41.059]    74\n",
      "Name: MEAN, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#等频离散\n",
    "d2=pd.qcut(data.MEAN,k)\n",
    "print(d2.value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7329bfd2",
   "metadata": {},
   "source": [
    "# 数据多维分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "20794474",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>市代码</th>\n",
       "      <th>市</th>\n",
       "      <th>类型</th>\n",
       "      <th>省</th>\n",
       "      <th>省代码</th>\n",
       "      <th>COUNT</th>\n",
       "      <th>AREA</th>\n",
       "      <th>MIN</th>\n",
       "      <th>MAX</th>\n",
       "      <th>RANGE</th>\n",
       "      <th>MEAN</th>\n",
       "      <th>STD</th>\n",
       "      <th>SUM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>200</td>\n",
       "      <td>440100</td>\n",
       "      <td>广州市</td>\n",
       "      <td>副省级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>6346.0</td>\n",
       "      <td>0.6346</td>\n",
       "      <td>21.100000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>14.900000</td>\n",
       "      <td>30.203703</td>\n",
       "      <td>2.461821</td>\n",
       "      <td>191672.69990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>201</td>\n",
       "      <td>440200</td>\n",
       "      <td>韶关市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>16444.0</td>\n",
       "      <td>1.6444</td>\n",
       "      <td>20.299999</td>\n",
       "      <td>31.200001</td>\n",
       "      <td>10.900002</td>\n",
       "      <td>26.348863</td>\n",
       "      <td>1.863408</td>\n",
       "      <td>433280.69980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>202</td>\n",
       "      <td>440300</td>\n",
       "      <td>深圳市</td>\n",
       "      <td>副省级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>1681.0</td>\n",
       "      <td>0.1681</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>29.100000</td>\n",
       "      <td>6.100000</td>\n",
       "      <td>25.793813</td>\n",
       "      <td>1.637604</td>\n",
       "      <td>43359.39999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>203</td>\n",
       "      <td>440400</td>\n",
       "      <td>珠海市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>1305.0</td>\n",
       "      <td>0.1305</td>\n",
       "      <td>21.100000</td>\n",
       "      <td>32.200001</td>\n",
       "      <td>11.100000</td>\n",
       "      <td>27.928966</td>\n",
       "      <td>1.528068</td>\n",
       "      <td>36447.30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>204</td>\n",
       "      <td>440500</td>\n",
       "      <td>汕头市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>1857.0</td>\n",
       "      <td>0.1857</td>\n",
       "      <td>22.799999</td>\n",
       "      <td>29.799999</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>25.586914</td>\n",
       "      <td>1.106098</td>\n",
       "      <td>47514.89999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>205</td>\n",
       "      <td>440600</td>\n",
       "      <td>佛山市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>3346.0</td>\n",
       "      <td>0.3346</td>\n",
       "      <td>26.600000</td>\n",
       "      <td>38.500000</td>\n",
       "      <td>11.900000</td>\n",
       "      <td>32.558637</td>\n",
       "      <td>1.579410</td>\n",
       "      <td>108941.19990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>206</td>\n",
       "      <td>440700</td>\n",
       "      <td>江门市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>8167.0</td>\n",
       "      <td>0.8167</td>\n",
       "      <td>23.700001</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>13.299999</td>\n",
       "      <td>29.529019</td>\n",
       "      <td>1.736622</td>\n",
       "      <td>241163.49980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>207</td>\n",
       "      <td>440800</td>\n",
       "      <td>湛江市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>10656.0</td>\n",
       "      <td>1.0656</td>\n",
       "      <td>19.400000</td>\n",
       "      <td>30.100000</td>\n",
       "      <td>10.700001</td>\n",
       "      <td>24.039649</td>\n",
       "      <td>2.020667</td>\n",
       "      <td>256166.49970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>208</td>\n",
       "      <td>440900</td>\n",
       "      <td>茂名市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>9910.0</td>\n",
       "      <td>0.9910</td>\n",
       "      <td>21.900000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>8.100000</td>\n",
       "      <td>25.719606</td>\n",
       "      <td>1.013216</td>\n",
       "      <td>254881.29990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>209</td>\n",
       "      <td>441200</td>\n",
       "      <td>肇庆市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>13167.0</td>\n",
       "      <td>1.3167</td>\n",
       "      <td>24.500000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>13.500000</td>\n",
       "      <td>28.875545</td>\n",
       "      <td>1.856796</td>\n",
       "      <td>380204.29990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>210</td>\n",
       "      <td>441300</td>\n",
       "      <td>惠州市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>9982.0</td>\n",
       "      <td>0.9982</td>\n",
       "      <td>19.900000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>13.100000</td>\n",
       "      <td>25.642597</td>\n",
       "      <td>2.081539</td>\n",
       "      <td>255964.39980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>211</td>\n",
       "      <td>441400</td>\n",
       "      <td>梅州市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>14101.0</td>\n",
       "      <td>1.4101</td>\n",
       "      <td>19.700001</td>\n",
       "      <td>27.400000</td>\n",
       "      <td>7.699999</td>\n",
       "      <td>23.802603</td>\n",
       "      <td>1.313515</td>\n",
       "      <td>335640.50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>212</td>\n",
       "      <td>441500</td>\n",
       "      <td>汕尾市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>4228.0</td>\n",
       "      <td>0.4228</td>\n",
       "      <td>21.400000</td>\n",
       "      <td>27.100000</td>\n",
       "      <td>5.700001</td>\n",
       "      <td>23.449196</td>\n",
       "      <td>0.913310</td>\n",
       "      <td>99143.19991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>213</td>\n",
       "      <td>441600</td>\n",
       "      <td>河源市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>13885.0</td>\n",
       "      <td>1.3885</td>\n",
       "      <td>20.200001</td>\n",
       "      <td>29.299999</td>\n",
       "      <td>9.099998</td>\n",
       "      <td>24.016673</td>\n",
       "      <td>1.422622</td>\n",
       "      <td>333471.50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>214</td>\n",
       "      <td>441700</td>\n",
       "      <td>阳江市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>6833.0</td>\n",
       "      <td>0.6833</td>\n",
       "      <td>22.200001</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>9.799999</td>\n",
       "      <td>27.512776</td>\n",
       "      <td>1.506371</td>\n",
       "      <td>187994.80000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>215</td>\n",
       "      <td>441800</td>\n",
       "      <td>清远市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>16929.0</td>\n",
       "      <td>1.6929</td>\n",
       "      <td>21.500000</td>\n",
       "      <td>31.600000</td>\n",
       "      <td>10.100000</td>\n",
       "      <td>27.847481</td>\n",
       "      <td>1.430775</td>\n",
       "      <td>471429.99990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>216</td>\n",
       "      <td>441900</td>\n",
       "      <td>东莞市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>2117.0</td>\n",
       "      <td>0.2117</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>35.299999</td>\n",
       "      <td>12.299999</td>\n",
       "      <td>29.875248</td>\n",
       "      <td>1.985548</td>\n",
       "      <td>63245.89997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>217</td>\n",
       "      <td>442000</td>\n",
       "      <td>中山市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>1520.0</td>\n",
       "      <td>0.1520</td>\n",
       "      <td>26.200001</td>\n",
       "      <td>36.099998</td>\n",
       "      <td>9.899998</td>\n",
       "      <td>28.628882</td>\n",
       "      <td>1.481816</td>\n",
       "      <td>43515.90001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>218</td>\n",
       "      <td>445100</td>\n",
       "      <td>潮州市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>2755.0</td>\n",
       "      <td>0.2755</td>\n",
       "      <td>23.100000</td>\n",
       "      <td>29.400000</td>\n",
       "      <td>6.299999</td>\n",
       "      <td>25.464537</td>\n",
       "      <td>1.224888</td>\n",
       "      <td>70154.79998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>219</td>\n",
       "      <td>445200</td>\n",
       "      <td>揭阳市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>4639.0</td>\n",
       "      <td>0.4639</td>\n",
       "      <td>21.700001</td>\n",
       "      <td>30.600000</td>\n",
       "      <td>8.900000</td>\n",
       "      <td>25.948782</td>\n",
       "      <td>2.057717</td>\n",
       "      <td>120376.40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>220</td>\n",
       "      <td>445300</td>\n",
       "      <td>云浮市</td>\n",
       "      <td>地级市</td>\n",
       "      <td>广东省</td>\n",
       "      <td>440000</td>\n",
       "      <td>6844.0</td>\n",
       "      <td>0.6844</td>\n",
       "      <td>24.600000</td>\n",
       "      <td>33.500000</td>\n",
       "      <td>8.900000</td>\n",
       "      <td>28.869565</td>\n",
       "      <td>1.686928</td>\n",
       "      <td>197583.29990</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     OBJECTID     市代码    市    类型    省     省代码    COUNT    AREA        MIN  \\\n",
       "201       200  440100  广州市  副省级市  广东省  440000   6346.0  0.6346  21.100000   \n",
       "202       201  440200  韶关市   地级市  广东省  440000  16444.0  1.6444  20.299999   \n",
       "203       202  440300  深圳市  副省级市  广东省  440000   1681.0  0.1681  23.000000   \n",
       "204       203  440400  珠海市   地级市  广东省  440000   1305.0  0.1305  21.100000   \n",
       "205       204  440500  汕头市   地级市  广东省  440000   1857.0  0.1857  22.799999   \n",
       "206       205  440600  佛山市   地级市  广东省  440000   3346.0  0.3346  26.600000   \n",
       "207       206  440700  江门市   地级市  广东省  440000   8167.0  0.8167  23.700001   \n",
       "208       207  440800  湛江市   地级市  广东省  440000  10656.0  1.0656  19.400000   \n",
       "209       208  440900  茂名市   地级市  广东省  440000   9910.0  0.9910  21.900000   \n",
       "210       209  441200  肇庆市   地级市  广东省  440000  13167.0  1.3167  24.500000   \n",
       "211       210  441300  惠州市   地级市  广东省  440000   9982.0  0.9982  19.900000   \n",
       "212       211  441400  梅州市   地级市  广东省  440000  14101.0  1.4101  19.700001   \n",
       "213       212  441500  汕尾市   地级市  广东省  440000   4228.0  0.4228  21.400000   \n",
       "214       213  441600  河源市   地级市  广东省  440000  13885.0  1.3885  20.200001   \n",
       "215       214  441700  阳江市   地级市  广东省  440000   6833.0  0.6833  22.200001   \n",
       "216       215  441800  清远市   地级市  广东省  440000  16929.0  1.6929  21.500000   \n",
       "217       216  441900  东莞市   地级市  广东省  440000   2117.0  0.2117  23.000000   \n",
       "218       217  442000  中山市   地级市  广东省  440000   1520.0  0.1520  26.200001   \n",
       "219       218  445100  潮州市   地级市  广东省  440000   2755.0  0.2755  23.100000   \n",
       "220       219  445200  揭阳市   地级市  广东省  440000   4639.0  0.4639  21.700001   \n",
       "221       220  445300  云浮市   地级市  广东省  440000   6844.0  0.6844  24.600000   \n",
       "\n",
       "           MAX      RANGE       MEAN       STD           SUM  \n",
       "201  36.000000  14.900000  30.203703  2.461821  191672.69990  \n",
       "202  31.200001  10.900002  26.348863  1.863408  433280.69980  \n",
       "203  29.100000   6.100000  25.793813  1.637604   43359.39999  \n",
       "204  32.200001  11.100000  27.928966  1.528068   36447.30000  \n",
       "205  29.799999   7.000000  25.586914  1.106098   47514.89999  \n",
       "206  38.500000  11.900000  32.558637  1.579410  108941.19990  \n",
       "207  37.000000  13.299999  29.529019  1.736622  241163.49980  \n",
       "208  30.100000  10.700001  24.039649  2.020667  256166.49970  \n",
       "209  30.000000   8.100000  25.719606  1.013216  254881.29990  \n",
       "210  38.000000  13.500000  28.875545  1.856796  380204.29990  \n",
       "211  33.000000  13.100000  25.642597  2.081539  255964.39980  \n",
       "212  27.400000   7.699999  23.802603  1.313515  335640.50000  \n",
       "213  27.100000   5.700001  23.449196  0.913310   99143.19991  \n",
       "214  29.299999   9.099998  24.016673  1.422622  333471.50000  \n",
       "215  32.000000   9.799999  27.512776  1.506371  187994.80000  \n",
       "216  31.600000  10.100000  27.847481  1.430775  471429.99990  \n",
       "217  35.299999  12.299999  29.875248  1.985548   63245.89997  \n",
       "218  36.099998   9.899998  28.628882  1.481816   43515.90001  \n",
       "219  29.400000   6.299999  25.464537  1.224888   70154.79998  \n",
       "220  30.600000   8.900000  25.948782  2.057717  120376.40000  \n",
       "221  33.500000   8.900000  28.869565  1.686928  197583.29990  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#切片\n",
    "#切片实际是在指定维度选择某一维度值后，来观察剩余维度的测度变化情况\n",
    "data[200:221]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "0dee6929",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({3: 85, 4: 13, 2: 151, 1: 98, 0: 25})"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#首先通过之前等距离散化获得的结果d1，统计各区间出现的次数\n",
    "from collections import Counter\n",
    "b = Counter(d1)\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3f12e0ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "labels = ['优','良','一般','稍差','较差']\n",
    "sizes = [25,98,150,86,14]\n",
    "\n",
    "plt.pie(sizes,labels = labels,autopct = '%1.1f%%',explode=(0.1,0.1,0,0,0))\n",
    "plt.title('全国各城市空气质量情况', fontdict={'fontsize':24},y=1.05)\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "25a2d79f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['font.sans-serif'] = ['Microsoft YaHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "x = data.市[200:221]\n",
    "y = data.MEAN[200:221]\n",
    "plt.barh(x, y, height=0.4,color = 'b')\n",
    "plt.title('广东各城市pm2.5密度', fontdict={'fontsize':24},y=1.05)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
